Description
Visa is searching for a Senior Manager, Data Science & Analytics - Global Marketing Services to build and own the data and intelligence layer for Marketing Services’ AI solutions and agents.
This role spans analytics and data science, combining deep analytical skills with AI data readiness expertise to convert VisaNet transaction data, client profile data, and market context into ranked, actionable growth opportunities.
Key Responsibilities
- Own the data and intelligence layer for AI solutions and agents: Design and build the end-to-end analytical solution that converts raw data into ranked, actionable client growth opportunities.
- Assess and prepare data for AI readiness: Evaluate data assets across VisaNet transaction data, client CRM and profile data, Visa Analytics Platform, and market intelligence sources.
- Build statistical and prediction models: Develop models for opportunity detection, root cause attribution, and opportunity sizing.
- Own the opportunity scoring framework: Design and maintain the scoring framework that ranks and surfaces actionable opportunities for business development teams.
- Co-own data integration with VisaNet and enterprise data sources: Partner with Visa Technology, VCA, and Insights and Analytics teams to integrate VisaNet transaction data, Visa Analytics Platform data, and client CRM and profile data into the intelligence layer.
- Ensure model documentation, validation, and governance: Partner with Responsible AI, Legal, Risk, Privacy, and Compliance teams to ensure models meet governance, regulatory, and Visa standards.
- Communicate insights and recommendations to stakeholders: Translate analytical findings and model outputs into clear, actionable recommendations for business stakeholders.
Qualifications
- 8 or more years of work experience with a Bachelor’s degree, or at least 6 years of work experience with an Advanced Degree, such as a Master’s or PhD in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related quantitative field.
- Experience spanning both analytics and data science, including exploratory data analysis, business intelligence, statistical modeling, and building predictive models in a production environment.
- Experience assessing data readiness for AI initiatives, including evaluating data quality, identifying gaps, defining data preparation requirements, and structuring data for AI consumption.
- Proficiency in Python, R, SQL, or similar languages for data analysis and statistical modeling, including experience with libraries such as scikit-learn, pandas, etc.
- Experience working with large-scale structured and unstructured datasets across multiple data sources, including transaction data, CRM data, and market intelligence.
- Experience building scoring frameworks, recommendation systems, or opportunity detection models that translate data into ranked, actionable business outputs.
- Experience with data governance, metadata management, data cataloging, or building data readiness frameworks for AI programs.
- Strong ability to translate complex analytical findings into clear business recommendations and stakeholder communications.